Streaming is a technology of processing transmitted data like a continuous flow of water without interruption. With the development of the Internet, streaming technology has become more and more important. The reason for this is that most users do not have high-speed interface lines sufficient to immediately download large capacity multimedia files. By utilizing streaming technology, a client browser or plug-in can begin the display of data even before all the files are transmitted.
Especially, demands for technology of streaming moving picture data have explosively increased on the wired Internet. Therefore, many service providers, such as Internet movie theaters or Internet broadcasting stations, have appeared. Differently from real-time conversation type communication, moving picture data streaming technology is characterized in that picture data to be transmitted is encoded in advance and stored in a server, and the playing of the moving picture data starts after an initial buffering time of approximately 5 through 20 seconds has elapsed when a request for the transmission of the moving picture data is received from a user.
Such streaming data consists of a plurality of packets which have several classes according to influences on service quality when the streaming data are displayed, or preset priorities of data. An operation of determining the classes and transmitting streaming data to clients according to the determined classes by a server is designated as packet scheduling.
There are two reference documents for the above-described streaming data scheduling: 1) ‘Markov decision process’ disclosed in “Rate-distortion optimized streaming of packetized media” by P. A. Chou and Z. Miao, submitted to IEEE Trans. Multimedia, February 2001 and 2) method disclosed in “Expected run-time distortion based scheduling for delivery of scalable media” by Z. Miao and A. Ortega, submitted to Int'l Packetvideo Workshop 2002, April 2002.
However, since the ‘Markov decision process’ disclosed in the reference document [1] uses a complicated algorithm, it is difficult to apply the ‘Markov decision process’ to streaming technology certainly requiring real-time implementation. The method disclosed in the reference document [2] is an algorithm of approximately and experientially calculating an expected value of video quality distortion in real-time, and then transmitting optimum video packets. For this algorithm, it is required to measure packet loss probability in real time. However, there is a problem in that it is difficult to measure the packet loss probability, so that performance of the algorithm is influenced by the precision of the measured packet loss probability.